Wind sensors can be used to measure a local wind velocity (e.g., wind direction and magnitude/speed) for stationary and/or moveable platforms. When a wind sensor is mounted to a stationary platform, such as a weather station mounted to a building and/or the ground, the wind velocity measured by the wind sensor is typically relatively stable and accurate. Such measurements may be used to provide reliable information about local environmental conditions. However, when a wind sensor is mounted to a moving platform, such as a vehicle, a mobile weather station, or an animal being studied in the wild, motion of the wind sensor can introduce noise and/or errors into the measured wind velocity. Inaccurate measurements of the local wind velocity can substantially reduce the capability of a data logging, user feedback, or control system relying on the measured wind velocity (e.g., as an input parameter for a vehicle control system, for example) to be an accurate measurement of local environmental conditions.
Various system methodologies have been developed to address motion-related noise in wind sensor data, but conventional methodologies typically introduce additional sources of error, such as measurement timing errors and/or errors in determining a position of the wind sensor relative to the moving platform. Under some conditions, the additional sources of error can reduce the system's overall accuracy to a level below that of an un-compensated system. Conventional steps taken to account for the newly introduced errors can increase the required complexity of the system so as to make it unsuitable for a number of uses, particularly for low-power and/or low-cost implementations. Thus, there is a need for an improved methodology to address wind sensor motion compensation.